Reduced intelligibility is the at the heart of the communication disorder associated with the dysarthrias and other speech production deficits, causing functional and societal limitations and disabilities, and undermining quality of life. At present, the most common clinical approach to intelligibility assessment is subjective in nature. Subjective impressions, although expedient to collect, are by their very nature vulnerable to clinician bias. Safeguards to enhance reliability and validity of subjective impressions (e.g., naive listeners, listen panels, etc) are prohibitively high cost for typical clinical settings. Thee is an urgent need for the development of dependent measures sensitive enough to detect speech changes in early disease;document the efficacy of behavioral, surgical or pharmacological interventions;and track speech changes associated with disease progression. In this translational research, we propose to use the well-developed principles of intelligibility quantification that have been standardized in speech telecommunications and to develop and validate new measures of intelligibility in clinical populations. Specifically, we aim to develop a process by which the intelligibility of dysarthric speech can be validly and reliably quantified relative to a reference control sample;and to algorithmically isolate the source(s) of intelligibiity degradation along certain dimensions to augment clinical practice. In addition to integrating existing intelligibility metrics within our developed framework, we intend to instantiate new metrics, specifically optimized for dysarthric speech, based on insight and data gained during a previous NIH-funded grant. Preliminary results show promise that the proposed approach will yield a successful framework for quantifying intelligibility. These results indicate existing telecommunication-based intelligibility metrics accurately capture intelligibility degradation for noisy speech. Further, we show that the same metrics can accurately capture differences in intelligibility between three dysarthric speakers of differing intelligibility levels. Finally, we how that a subset of the envelope modulation spectra features, developed previously in our lab, are remarkably predictive of a speaker's intelligibility. The results of the proposed research will for the basis for a subsequent R01 proposal for the development of a fully functional clinical tool to objectively quantify and track speech intelligibility and its causal components.
There is an urgent need for the development of dependent measures sensitive enough to detect speech changes in early disease;document the efficacy of behavioral, surgical or pharmacological interventions;and track speech changes associated with disease progression. Reduced intelligibility is the at the heart of the communication disorder associated with the dysarthrias and other speech production deficits, causing functional and societal limitations and disabilities, and undermining quality of life. We aim to develop a process by which the intelligibility of dysarthric speech can be validly and reliably quantified relative to a reference control sample;and to algorithmically isolate the source(s) of intelligibiity degradation along certain dimensions to augment clinical practice.
| Berisha, Visar; Wisler, Alan; Hero, Alfred O et al. (2016) Empirically Estimable Classification Bounds Based on a Nonparametric Divergence Measure. IEEE Trans Signal Process 64:580-591 |
| Lansford, Kaitlin L; Berisha, Visar; Utianski, Rene L (2016) Modeling listener perception of speaker similarity in dysarthria. J Acoust Soc Am 139:EL209 |
| Jiao, Yishan; Berisha, Visar; Tu, Ming et al. (2015) Convex weighting criteria for speaking rate estimation. IEEE/ACM Trans Audio Speech Lang Process 23:1421-1430 |
| Lansford, Kaitlin L; Liss, Julie M (2014) Vowel acoustics in dysarthria: mapping to perception. J Speech Lang Hear Res 57:68-80 |
| Berisha, Visar; Liss, Julie; Sandoval, Steven et al. (2014) Modeling Pathological Speech Perception From Data With Similarity Labels. Proc IEEE Int Conf Acoust Speech Signal Process 2014:915-919 |
| Berisha, Visar; Sandoval, Steven; Utianski, Rene et al. (2014) Characterizing the distribution of the quadrilateral vowel space area. J Acoust Soc Am 135:421-7 |
| Berisha, Visar; Utianski, Rene; Liss, Julie (2013) Towards A Clinical Tool For Automatic Intelligibility Assessment. Proc IEEE Int Conf Acoust Speech Signal Process :2825-2828 |
| Berisha, Visar; Sandoval, Steven; Utianski, Rene et al. (2013) Selecting Disorder-Specific Features for Speech Pathology Fingerprinting. Proc IEEE Int Conf Acoust Speech Signal Process :7562-7566 |
| Sandoval, Steven; Berisha, Visar; Utianski, Rene L et al. (2013) Automatic assessment of vowel space area. J Acoust Soc Am 134:EL477-83 |
| Borrie, Stephanie A; McAuliffe, Megan J; Liss, Julie M et al. (2012) Familiarisation conditions and the mechanisms that underlie improved recognition of dysarthric speech. Lang Cogn Process 27:1039-1055 |
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